@article{ref1,
title="An improved approach for association rule mining using a multi-criteria decision support system: a case study in road safety",
journal="European transport research review",
year="2017",
author="Ait-Mlouk, Addi and Gharnati, Fatima and Agouti, Tarik",
volume="9",
number="3",
pages="e40-e40",
abstract="PURPOSERoad accidents have come to be considered a major public health problem worldwide. The aim of many studies is therefore to identify the main factors contributing to the severity of crashes.<br><br>METHODSThis paper examines a large-scale data mining technique known as association rule mining, which can predict future accidents in advance and allow drivers to avoid the dangers. However, this technique produces a very large number of decision rules, preventing decision makers from making their own selection of the most relevant rules. In this context, the integration of a multi-criteria decision analysis approach would be particularly useful for decision makers affected by the redundancy of the extracted rules.<br><br>CONCLUSIONAn analysis of road accidents in the province of Marrakech (Morocco) between 2004 and 2014 shows that the proposed approach serves this purpose; it may provide meaningful information that could help in developing suitable prevention policies to improve road safety.<p /> <p>Language: en</p>",
language="en",
issn="1867-0717",
doi="10.1007/s12544-017-0257-5",
url="http://dx.doi.org/10.1007/s12544-017-0257-5"
}